Data for companies or other organizations is commonly stored in networked storage. The resources for storage and access bandwidth are limited. However, the amount of data and the desire to access data more quickly (i.e., in terms of time for access) and more efficiently (i.e., in terms of power and processing load) are all increasing. Thus, a common goal for a data center that stores and manages the networked data is to improve utilization of the resources of the networked storage, to improve storage utilization and access throughput.
The data access management of the data can implement service level objectives (SLOs) that define performance requirements for certain workloads or users, and can also implement caching of frequently used data. The data access management manages access to the data through file layout techniques, which define how the data is stored and accessed in a system. However, traditional data access management uses a single common file layout for all data in the system. Traditionally, the data representation by the file layout is closely coupled to the physical layout of the data in storage resources.
While a file layout can be made to efficiently share data in a networked storage system, it will be understood that the complexity and implementation costs of including access optimizations in a single common file layout for access to multiple different data types are prohibitive. The complexity and implementation costs are especially high when considering that data of different types or the same type can have different SLOs. Thus, traditional file layout for data access management of necessity works better for some data access scenarios than others. If the techniques of such a traditional file layout were used to manage data access for a cache, the effectiveness of the caching may be significantly lower than desired.